Bimanual motor skill learning and robotic assistance for chronic hemiparetic stroke: a randomized controlled trial

Using robotic devices might improve recovery post-stroke, but the optimal way to apply robotic assistance has yet to be determined. The current study aimed to investigate whether training under the robotic active-assisted mode improves bimanual motor skill learning(biMSkL) more than training under the active mode in stroke patients. Twenty-six healthy individuals(HI) and 23 chronic hemiparetic stroke patients with a detectable lesion on MRI or CT scan, who demonstrated motor deficits in the upper limb, were randomly allocated to two parallel groups. The protocol included a two-day training on a new bimanual cooperative task, LIFT-THE-TRAY, under either the active or activeassisted modes(where assistance decreased in a pre-determined stepwise fashion) with the bimanual version of the REAplan? robotic device. The hypothesis was that the active-assisted mode would result in greater biMSkL than the active mode. The biMSkL was quantified by a speed-accuracy trade-off(SAT) before(T1) and immediately after(T2) training on days 1 and 2(T3 and T4). The change in SAT after 2 days of training(T4/T1) indicated that both HI and stroke patients learned and retained the bimanual cooperative task. After 2 days of training, the active-assisted mode did not improve biMSkL more than the active mode(T4/T1) in HI nor stroke patients. Whereas HI generalized the learned bimanual skill to different execution speeds in both the active and active-assisted subgroups, the stroke patients generalized the learned skill only in the active subgroup. Taken together, the active-assisted mode, applied in a pre-determined stepwise decreasing fashion, did not improve biMSkL more than the active mode in HI and stroke subjects. Stroke subjects might benefit more from robotic assistance when applied "as-needed." This study was approved by the local ethical committee(Comité d'éthique médicale, CHU UCL Namur, MontGodinne, Yvoir, Belgium;Internal number: 54/2010, Eudra CT number: NUB B039201317382) on July 14, 2016 and was registered with ClinicalTrials.gov(Identifier: NCT03974750) on June 5, 2019.

A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recognition System(TSRS)is one of themost important components ofADAS.Among the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time.Accordingly,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules.Firstly,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured frames.Secondly,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise recognition.In addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting technique.Through rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,respectively.Furthermore,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

How a Computer Assists English Teaching and Learning among Vocational Colleges

"College English Curriculum Requirements", edited by Department of Higher Education(2007), put forward clearly one of the key points of the national College English teaching reform was to strengthen the application of computer to college English teaching and apply computer-and-classroom-based English teaching mode, improving the previous mode dominated by a single teacher. Most colleges and universities in China have basically achieved the popularity of computer multimedia classrooms and campus networks. However, according to researches(Xia, 2002), most teachers still hold the main role of them in classes as"language interpreter"and"language instructor". Although advanced computer technology has been provided, most teachers feel confused or difficult in using it to assist their English teaching efficiently. As a consequence, computer technology fail to play its role in English classes. Driven by the great development of science and technology, computer has brought about incredible changes in every aspect of social life since 1980 s. In current times, almost every aspect of college students' life has been closely associated with computer. However, in most situations, computer is not taken as a typical language learning tool in their daily life. It is known that most students' English basis is relatively weak in vocational colleges; meanwhile, the way in which they learned English during the middle school period was basically translation- based teaching. Thus they have little or even no interest in English learning at all. In this way, discovering a new and interesting way with the aid of computer to learn English is of essential importance. Based on this, the paper discusses five major aspects under the circumstance of computer-assisted English learning. It is hoped that vocational college English teaching and learning can become more efficient by means of computer technology, finally students' English learning motivation and English competence can be enhanced to a great extent.

多无人机辅助边缘计算场景下基于Q-learning的任务卸载优化

引入多无人机辅助边缘计算系统,由多个无人机和原有边缘服务器共同为移动用户提供通信和计算资源;将优化问题建模为资源竞争和卸载决策约束下的系统总效用最大化问题,系统总效用由用户满意度、任务延迟和系统能耗3个因素组成.由于优化模型是一个具有NP难属性的非凸问题,故采用强化学习方法求解得到使系统总效用最大的最优任务卸载决策集.仿真实验结果表明,与贪心顺序调优卸载方案和随机选择卸载方案相比,该文提出的Q-learning方案的系统总效用分别提高了15%和43%以上.

Computer Assisted Language Learning Social Networks: What Are They Talking about?

There are many reasons that motivate people to build online communities. The purpose of this study was to identify the topics that learners discuss when they are part of a computer assisted language learning course in order to answer the question “What are they talking about?”. We have examined an e-community of 618 students who were learning the Modern Greek language online. We analyzed their conversation topics directly from the discussion boards of the web-based course and sorted them into the pre-defined topic categories. The results of the study showed that during the first lessons of the course the students contributed more to social discussions which were unrelated to the course material. The reason of this outcome is that the students want to introduce themselves and meet their peers. As they progressed through the course’s lessons, however, their discussion topics became more course material related. The study ends with implications of the results and future research directions.

Learning curve for hand-assisted laparoscopic D2 radical gastrectomy

AIM:To describe the learning curves of hand-assisted laparoscopic D2 radical gastrectomy(HALG) for the treatment of gastric cancer.METHODS:The HALG surgical procedure consists of three stages:surgery under direct vision via the port for hand assistance,hand-assisted laparoscopicsurgery,and gastrointestinal tract reconstruction.According to the order of the date of surgery,patients were divided into 6 groups(A-F) with 20 cases in each group.All surgeries were performed by the same group of surgeons.We performed a comprehensive and indepth retrospective comparative analysis of the clinical data of all patients,with the clinical data including general patient information and intraoperative and postoperative observation indicators.RESULTS:There were no differences in the basic information among the patient groups(P > 0.05).The operative time of the hand-assisted surgery stage in group A was 8-10 min longer than the other groups,with the difference being statistically significant(P = 0.01).There were no differences in total operative time between the groups(P = 0.30).Postoperative intestinal function recovery time in group A was longer than that of other groups(P = 0.02).Lengths of hospital stay and surgical quality indicators(such as intraoperative blood loss,numbers of detected lymph nodes,intraoperative side injury,postoperative complications,reoperation rate,and readmission rate 30 d after surgery) were not significantly different among the groups.CONCLUSION:HALG is a surgical procedure that can be easily mastered,with a learning curve closely related to the operative time of the hand-assisted laparoscopic surgery stage.

Peer-assisted learning to train high-school students to perform basic life-support

BACKGROUND: The inclusion of cardiopulmonary resuscitation(CPR) in formal education has been a useful approach to providing basic life support(BLS) services. However, because not all students have been able to learn directly from certified instructors, we studied the educational efficacy of the use of peer-assisted learning(PAL) to train high-school students to perform BLS services.METHODS: This study consisted of 187 high-school students: 68 participants served as a control group and received a 1-hour BLS training from a school nurse, and 119 were included in a PAL group and received a 1-hour CPR training from a PAL leader. Participants' BLS training was preceded by the completion of questionnaires regarding their background. Three months after the training, the participants were asked to respond to questionnaires about their willingness to perform CPR on bystander CPR and their retention of knowledge of BLS.RESULTS: We found no statistically significant difference between the control and PAL groups in their willingness to perform CPR on bystanders(control: 55.2%, PAL: 64.7%, P=0.202). The PAL group was not significantly different from the control group(control: 60.78±39.77, PAL: 61.76±17.80, P=0.848) in retention of knowledge about BLS services.CONCLUSION: In educating high school students about BLS, there was no significant difference between PAL and traditional education in increasing the willingness to provide CPR to bystanders or the ability to retain knowledge about BLS.

Highway Foreign Body Intrusion Detection System Based on Deep Learning

This paper introduces the expressway intrusion detection system based on deep learning to improve traffic safety.The system adopts deep learning,image recognition,and foreign body detection technology to monitor the road condition in real-time through lidar and binocular camera groups to detect and distance the foreign body on the road.The system visualizes the detection results on the onboard screen to assist the driver to avoid and improve the safety of highway driving.In addition,the system also includes emergency braking,blind spot monitoring,lane departure warning,and other functions.The system has wide application prospects and development potential and is expected to be widely used in the future,providing a strong guarantee for the safe operation of expressways in China.

A Study on Diagnostic Assist Systems of Chronic Obstructive Pulmonary Disease from Medical Images by Deep Learning

In this paper, we propose new diagnostic assist systems of medical images using deep learning algorithms. Specifically, we aim to develop a diagnostic support system for the very early stage of chronic obstructive pulmonary disease (COPD) based on the CT images. It is said that COPD is a disease that develops due to long-term smoking, and it is said that there are a large number of latent onset reserve forces. By discovering this COPD in the very early period 0 and improving the living conditions, subsequent severity can be avoided in many cases, so a system that will help diagnosis by professional radiologists is needed. We show the some experimental results examined by the constructed system.

Computer Assisted Learning for Improving Cattle Palpation Skills of Veterinary Students

This study investigated the effect of a computer assisted learning (CAL) tool on the development of skills in palpation of the reproductive tract of the cow per rectum (rectal palpation) by fourth-year students in a Bachelor of Veterinary Science (BVSc) degree program. A secondary aim was to determine if animal welfare could be improved by the CAL intervention. The CAL tool was developed to provide: vivid, three-dimensional interactive graphics of the relevant anatomy and skills;a comprehensive glossary of terminology used in association with the skills;and formative assessment tasks. Prior to its introduction to the course, industry stakeholders assessed the CAL tool graphics as an accurate depiction of the procedures. Two consecutive cohorts of students were surveyed prior to (n = 91) and after the CAL intervention (n = 111). Responses to student surveys suggested that post-intervention skills were learned at approximately the same rate as pre-intervention. However, tutor surveys indicated that students in the pre-intervention group may have had insufficient understanding for accurate self-assessment compared to post-intervention students. According to tutors, substantially more students in the post-intervention group gained practical skills at an improved rate and to a higher level of competency. Both student and tutor surveys indicated that there was a minimal discomfort to animals in these practical classes. From an animal welfare point-of-view, it was concluded that the intervention would not result in a reduction in the number of animals required during practical sessions. However, due to the preparation and reinforcement provided by the CAL tool, animals were used more efficiently by students after the intervention, resulting in the attainment of a higher level of skill. Knowledge gained from this study may be relevant to other disciplines requiring students to develop practical skills associated with animals or humans.

Integration of Computer Assisted Learning in Teaching and Learning in Secondary Schools in Kenya

The purpose of this study was to establish factors that lead to poor integration of Information and communication technology （ICT） for teaching and learning in schools in Kenya, despite comprehensive policy, institutional, infrastructural frameworks and capacity building by the Ministry of Education. The subject of this study was administered by use of questionnaires in three categories of public schools： national school, provincial schools and district schools. The respondents were students from each level that is from one, two, three and four and teachers based on the most offered subjects in the secondary schools. The computer assisted learning facilities were classified into computers, internet and content in optical media. In national school Internet based research, optical media content provided by Kenya Institute of Curriculum Development and Cyber School program for science subjects was used in learning. In provincial school, it lacks adequate computers, reliable Internet and content in optical media. In district school, it lacks adequate computer, no internet connection and content in optical media. A learner management system which can be accessed by all learners by use of any internet access devices like mobile phone access will be an ideal tool with over 4,000,000 mobile phone subscribers currently in Kenya.

Direct Instruction by an Experienced Surgeon Can Shorten the Learning Curve for Laparoscopic-Assisted Distal Gastrectomy

Aim: Laparoscopy-assisted distal gastrectomy (LADG) with regional lymph node dissection is a treatment option for patient with early gastric cancer. However, LADG is a technically complex and advanced procedure, which is challenging for inexperienced surgeons. In this report, we retrospectively evaluated the learning curve for LADG of a single surgeon with no previous experience in LADG and the usefulness of direct instruction by a surgeon experienced in LADG in shortening the learning curve. Patients and Methods: This study was analyzed 80 consecutive patients, who underwent LADG by a single surgeon (first assistant in 10 cases and operator in 70 cases) between January 2008 and December 2012. Patients were divided into 3 sequential groups of 10 (training period), 30 (learning period), and 40 (operating period) cases in each group. Median operation time and estimated blood loss for these 3 groups were determined. Other learning indicators, including transfusion requirement, postoperative complications, number of lymph node harvested, and rate of conversion open gastrectomy, were also evaluated. Results: During the training period, median operation time and estimated blood loss were 219.5 min and 83.0 ml, respectively. During the learning period, the operation time was significantly longer than that of training period. In the operating period, the operation time was significantly lesser than that during the learning period. However, the operation time was not different from that during the training period and reached a plateau. The estimated blood loss during the operating period was significantly lesser than that during the learning period. The difference in the number of lymph nodes retrieved between each group was not significant. Conclusions: Direct instructions by an experienced surgeon can decrease the number of cases required for learning. Because LADG is technically more complex than other laparoscopic procedures, standardization of LADG and an effective training system for performing it should be established.

Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy

Assisted diagnosis using artificial intelligence has been a holy grail in medical research for many years, and recent developments in computer hardware have enabled the narrower area of machine learning to equip clinicians with potentially useful tools for computer assisted diagnosis(CAD) systems. However, training and assessing a computer's ability to diagnose like a human are complex tasks, and successful outcomes depend on various factors. We have focused our work on gastrointestinal(GI) endoscopy because it is a cornerstone for diagnosis and treatment of diseases of the GI tract. About 2.8 million luminal GI(esophageal, stomach, colorectal) cancers are detected globally every year, and although substantial technical improvements in endoscopes have been made over the last 10-15 years, a major limitation of endoscopic examinations remains operator variation. This translates into a substantial inter-observer variation in the detection and assessment of mucosal lesions, causing among other things an average polyp miss-rate of 20% in the colon and thus the subsequent development of a number of post-colonoscopy colorectal cancers. CAD systems might eliminate this variation and lead to more accurate diagnoses. In this editorial, we point out some of the current challenges in the development of efficient computer-based digital assistants. We give examples of proposed tools using various techniques, identify current challenges, and give suggestions for the development and assessment of future CAD systems.

Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.

Educational Application for Special Needs Is a Learning Tool the Way Forward？

As the 21st century brings in a revolutionary change in the way students study at schools and universities, technology continues to play a crucial role in helping students achieve more conceptual and practical knowledge of topics taught in classrooms. Students with special needs too are now able to study in a general classroom setting, access relevant technologies and use them for higher cognitive development, helping them integrate with their surroundings. However, existing literature shows that though multiple learning tools exist that do enhance learning in special needs students, they either cater to specific areas of development such as Mathematics and English, or that are targeted towards a specified category of studentswith special needs such as autism and cerebral palsy. Furthermore, despite multiple laws and regulations supporting the right to education launched by the UAE （United Arab Emirates） government for special needs students, there seems to exist a need to provide classrooms across the country with educational applications that have a universal approach particularly in the UAE in order to include students with almost any special needs. This paper looks closely at the existing literature and highlights this gap, especially in the UAE and proposes to develop such a tool based on existing learning concepts.

Conducting the Task-based Approach With Context Aware Mobile Situated Learning on Learning English for College Students＇ Learning Performance

Learning English with specific purpose （ESP） initiatives domain knowledge and language ability with English learning to meet future job demands （Leroux ＆ Lafleur, 1995; Khan ＆ Khan, 2015）. In the information age, the innovative technologies of mobile devices make the dramatical changes in ways of teaching and learning （Atkinson, 2011; Bierstaker, Janvrin ＆ Lowe, 2014, Pittaway, 2012; Yang ＆ Che, 2015）. The focus of this study aims to examine ESP college students＇ English learning performance by using Context Aware Mobile Situated Learning （CAMSL） in Tourism and Hospitality Management field and other majors. The mixed research method is conducted for data collection and analysis. The quantitative data are collected by examining students＇ learning performance; the qualitative data are allowed to understand the students＇ perspective toward their role in using the CAMSL with Tourism related content. Eight-three students are randomly selected and divided into two groups： 42 students are assigned in the experimental group A （CAMSL）, and 41 students are assigned in control group. Two groups of students receive pretest and posttest to examine their English performance. Besides, twenty students from group A and B are selected for online survey. The survey is mailed directly to students＇ email account. Results represented by using CAMSL show the significant improvement on students＇ learning performance. In addition, the survey data indicate the benefits of using the CAMSL help students enhance their academic discourse, develop their learned knowledge to represent their profession, use English properly to speak themselves up, and provide the effectiveness of obtain domain knowledge in future workplace.

Interactive Peer Learning In An English Immersion Context In China

English immersion in the mainland of China has started in Xi＇an since the late 1990s, and extended into other cities in the mainland of China. This study reported the findings of the students＇ interactive peer learning model in the immersion programs, such as peer prompting and waiting; non-verbal expressions; correcting errors and modulating speaking volume; translation; attending to the peer interlocutor＇ s needs; and reciprocating peer assistance.

A Study on the Cultivation Path of English Learning Initiative Ability of Xinjiang Students

The“counterpart aid to Xinjiang”is one of the important measures to implement the country’s western development strategy.It aims to shorten the gap between higher education in Xinjiang and the eastern region and to maintain the coordinated development of education,economy and society in the eastern and western regions.This article takes the counterpart support of Xinjiang students from the School of Foreign Languages of Jilin Engineering Normal University as an example to explore the problem of the initiative training of Xinjiang students in English learning in our school,mainly from the aspects of the students themselves,the teachers and the entire education and training environment of our school.The angle explains how to help them improve their learning initiative.This article is divided into three parts.The first is the analysis of the connotation of learning initiative;the second is its meaning;the last is how to build the learning initiative of Xinjiang students.

Focus on the Language Learner and Multimedia Assisted Language Teaching

当外语教师在试图寻找一种合适的外语教学方法的时候,他们会经常失望的发现现存的教学方法没有一种单独使用效果好并且能够满足所有学习者的要求,放之天下而皆准。因此,第二语言教学将目光从研究教学法中转移到研究学习者的身上来,关注学生的智力、学能、认知风格、学习策略等方面,以便最大限度地帮助学生。笔者从语言学、心理学、二语习得理论及人本主义教学理论等方面探讨了以学习者为中心这一教学原则的理论基础及其集中体现了这一教学思想的多媒体辅助教学。

LEARNS模式联合盆底肌训练在机器人辅助根治性前列腺切除术患者中的应用价值

目的:分析探讨LEARNS模式的护理方案联合盆底肌训练(PFMT)在机器人辅助根治性前列腺切除术(RARP)患者中的应用价值。方法:选取2019年1月—2023年10月在深圳市人民医院接受RARP的患者122例。随机分为研究组和对照组,每组各61例。对照组接受常规根治性前列腺切除术后PFMT健康教育方案,研究组接受LEARNS模式联合PFMT方案。比较两组患者的排尿功能指标、I-QOL评分、自我照护量表评分以及并发症发生情况。结果:干预前,两组患者各项排尿功能指标、I-QOL评分和自我照护量表评分差异均无统计学意义;干预后,两组患者排尿功能指标、I-QOL评分和自我照护量表评分均优于干预前,且研究组优于对照组;研究组并发症发生率低于对照组。结论:与传统护理方案相比,采用LEARNS模式的护理方案联合PFMT应用于RARP患者,能够改善患者排尿功能,提高生活质量,促进患者自我照护能力恢复,有效控制并发症发生率,具有临床推广应用意义。